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Moving Beyond Widgets : Measuring for Outcomes in Social Services

Moving Beyond Widgets : Measuring for Outcomes in Social Services. The AIDS Foundation of Chicago Experience David Munar and Keri Rainsberger Michael Reese Health Trust Health Care Issues Roundtable February 24, 2012. AIDS Foundation of Chicago.

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Moving Beyond Widgets : Measuring for Outcomes in Social Services

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  1. Moving Beyond Widgets : Measuring for Outcomes in Social Services The AIDS Foundation of Chicago Experience David Munar and Keri Rainsberger Michael Reese Health Trust Health Care Issues Roundtable February 24, 2012

  2. AIDS Foundation of Chicago The mission of the AIDS Foundation of Chicago is to lead the fight against HIV/AIDS and improve the lives of people affected by the epidemic. Founded in 1985 by community activists and physicians, the AIDS Foundation of Chicago (AFC) is a local and national leader in the fight against HIV/AIDS. We collaborate with community organizations to develop and improve HIV/AIDS services; fund and coordinate prevention, care, and advocacy projects; and champion effective, compassionate HIV/AIDS policy.

  3. Social Service Databases • ClientTrack – AFC’s Client-Level Database • Client-level information on case management and supportive services • Used by the Northeastern Illinois HIV/AIDS Case Management Cooperative and the AIDS Foundation of Chicago housing programs • Homeless Management Information Systems (HMIS) • Client-level information on homeless persons and their service needs • Required by the US Department of Housing and Urban Development (HUD) and implemented by local continuum • AFC participates in the City of Chicago continuum database (ServicePoint). There are also separate HMIS implementations in most of the suburban counties and a few of the larger suburbs

  4. City of Chicago HMIS Implemented and operated by the Chicago Department of Family and Support Services (DFSS) with support from many others All HUD-funded programs are required to participate; other homeless service providers are encouraged to participate The City of Chicago’s federal homeless funding is tied partially to the success of HMIS AFC participates as an Interface agency by automatically uploading data on a regular basis. AFC also logs in directly to verify data was imported correctly

  5. ClientTrack: Multiple Partners and Users 258 users 13 programs 26 grants 37 agencies ClientTrack

  6. ClientTrack: Capturing Service Encounter and Outcomes Data

  7. Example Tracking Client Care • 11/28 • Initial referral • Newly diagnosed • Assigned to agency same day • 2/2 • Follow-up call from CM • Client reports taking HIV medications • 12/7 • Intake • Set goals to obtain medical care and ADAP • CM calls clinic on client’s behalf to schedule first appointment • 12/16 • CM receives medical form verifying appointment and medical information • 11/29 • Call setting initial intake This is a real example from one of our clients flowing through care. For most of our clients this flow is more complex with multiple issues being addressed.

  8. Tracking Care at a System Level System level uses of data • Understand how case management is being implemented • Able to measure how system is comparing to standards of care • Estimate impacts of policy or procedure changes • Estimate eligible population for new services • Easier and more in-depth reporting Data from July-December 2011

  9. Moving Toward Data Integration Service data is entered and reported to multiple databases Integration includes both the physical sharing of the data but also policies governing the sharing ClientTrack as a “data warehouse”

  10. AFC’s Visions for Future Development:Data coordination • Surveillance • HMIS • Client • Client • Track • ADAP • Medicaid • EMR • Opportunities abound for additional data coordination • Shared definitions and standards important • Client confidentiality in an era of increased data sharing

  11. AFC’s Visions for Future Development:Greater data analysis capabilities • Assessing for outcomes • Clients assessed every 6 months • Researcher analyzing questions to see what outcomes we might be able to pull from this data • Analyzing processes • Where do clients hit snags in receiving needed services • Is data being entered correctly • Challenges of working with administrative data • Geared to users not researchers • Multiple sources of entry • Retrospective • In the “wild” rather than a laboratory

  12. AFC’s Visions for Future Development:Robust quality improvement process • Automated chart audits • Implemented first stage this round • Allows review of 100% of charts virtually • Will be made available to agencies to do their own interim reviews • Quality Management Reports • Medical Case Management standards established • Reports for users at multiple levels (case managers, agency supervisors, AFC program coordinators)

  13. Example Quality Improvement • Medical Case Manager Standards • Developed from best practices, consultation with key informants • Based on a one year period, most standards require two instances within the year • Case Management Face-to-Face Visits (CM V) • Medical Visits (Med V) • Case Management Assessments (CM AS) • Care Plan Development and Update (CARE P) • Care Plan Has Medical Goal (MED G) • Adherence Counseling Provided (ADHER) • Communication between Primary Care Provider and Case Manager (PCP C)

  14. Example Quality Improvement Case Manager Tools : Indicators Check List Case Manager Tools : To Do List

  15. Example Agency Indicator Review

  16. Example Quality Improvement System Indicator Review (used by agencies and AFC)

  17. Example Quality Improvement AFC Program Coordinator indicator review

  18. Challenges and lessons learned • The “Rich Silo” effect • Non-cooperation and gamesmanship between data sources creates detailed data that is still not shared • Quality data requires culture change • Requires a whole process outlook • Balancing privacy and confidentiality with increasing capabilities • Consider the need to know and usefulness before collecting data • Ensuring client consents and education keep up with sharing capacity • Standardization • Data can require a significant amount of recoding to be shared across databases • Ensuring programs are being integrated in a consistent way across providers • Deduplication

  19. Acknowledgements Over 6000 clients who shared their data with us 258 users who enter and check data The AFC Research Evaluation and Data Services, Care, and Housing Teams

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